Case-Control Studies of Genetic and Environmental Factors with Error in Measurement of Environmental Factors

• Activity Number: 591
• Type: Invited
• Date/Time: Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Iryna Lobach*+ and Raymond James Carroll and Spinka Christie and Mitchell Gail and Nilanjan Chatterjee
• Companies: New York University and Texas A & M University and Missouri University and National Cancer Institute and National Cancer Institute

Abstract

It is widely believed that risks of many complex diseases are determined by genetic susceptibilities, including environmental exposures, and their interaction. We develop a semiparametric maximum-likelihood approach to analysis of case-control studies of gene-environment interactions in the situations when some of the environmental covariates are measured with error, and allow genetic information to be missing on some subjects, e.g., unphased haplotypes. Profile likelihood techniques and an EM algorithm are developed, resulting in a relatively simple procedure for parameter estimation. We prove consistency and derive the resulting asymptotic covariance matrix of parameter estimates. Performance of the proposed procedure is demonstrated using a series of simulation experiments. Application of the approach is demonstrated using a case-control study of colorectal adenoma.